Top Concerns of Tweeters During the COVID-19 Pandemic: Infoveillance Study
Top Concerns of Tweeters During the COVID-19 Pandemic: Infoveillance Study
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DOI：
10.2196/19016
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发表时间：
2020-04-21
影响因子：
7.4
通讯作者：
Shah, Zubair
中科院分区：
文献类型：
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作者：
Abd-Alrazaq, Alaa;Alhuwail, Dari;Shah, Zubair
背景资料：最近的冠状病毒病（COVID-19）大流行正在对世界卫生保健基础设施以及人类的社会，经济和心理健康造成损害。个人、组织和政府正在使用社交媒体就与COVID-19大流行有关的多个问题相互沟通。关于社交媒体平台上分享的与COVID-19相关的话题，我们知之甚少。分析这些信息可以帮助政策制定者和医疗保健组织评估其利益相关者的需求，并适当地解决这些需求。目的：本研究旨在确定Twitter用户发布的与COVID-19大流行相关的主要主题。方法：利用一套工具（Twitter的搜索应用程序编程接口（API）、TweetPythonlibrary、和PostgreSQL数据库），并使用一组预定义的搜索项（“corona”，“2019-nCov”和“COVID-19”），我们提取了文本和元数据（喜欢和转发的数量，以及包括关注者数量在内的用户个人资料信息）从2020年2月2日到3月15日的公共英语推文，2020.我们使用单字（unigrams）和双字（bigrams）的词频分析了收集到的推文。我们利用潜在Dirichlet分配进行主题建模，以识别推文中讨论的主题。我们还进行了情感分析，提取了每个主题的平均转发数、喜欢数和关注数，并计算了每个主题的互动率。结果：在大约280万条推文中，来自160，829个独立用户的167，073条独立推文符合纳入标准。我们的分析确定了12个主题，分为四个主题：病毒的起源;其来源;其对人，国家和经济的影响;以及减轻感染风险的方法。10个主题的平均情绪为正面，2个主题为负面（COVID-19造成的死亡和种族主义增加）。推特账号关注者的平均推特主题从2722（种族主义增加）到13,413（经济损失）不等。推特的最高平均点赞数为15.4（经济损失），最低为3.94（旅行禁令和警告）。结论：实地和网上的公共卫生危机应对活动正变得越来越同步和交织。社交媒体提供了直接向公众传达健康信息的机会。卫生系统应通过监测社交媒体，努力建立国家和国际疾病检测和监测系统。还需要在社交媒体上建立更积极主动和灵活的公共卫生存在，以打击假新闻的传播。
Background: The recent coronavirus disease (COVID-19) pandemic is taking a toll on the world's health care infrastructure as well as the social, economic, and psychological well-being of humanity. Individuals, organizations, and governments are using social media to communicate with each other on a number of issues relating to the COVID-19 pandemic. Not much is known about the topics being shared on social media platforms relating to COVID-19. Analyzing such information can help policy makers and health care organizations assess the needs of their stakeholders and address them appropriately.Objective: This study aims to identify the main topics posted by Twitter users related to the COVID-19 pandemic.Methods: Leveraging a set of tools (Twitter's search application programming interface (API), Tweepy Python library, and PostgreSQL database) and using a set of predefined search terms ("corona," "2019-nCov," and "COVID-19"), we extracted the text and metadata (number of likes and retweets, and user profile information including the number of followers) of public English language tweets from February 2, 2020, to March 15, 2020. We analyzed the collected tweets using word frequencies of single (unigrams) and double words (bigrams). We leveraged latent Dirichlet allocation for topic modeling to identify topics discussed in the tweets. We also performed sentiment analysis and extracted the mean number of retweets, likes, and followers for each topic and calculated the interaction rate per topic.Results: Out of approximately 2.8 million tweets included, 167,073 unique tweets from 160,829 unique users met the inclusion criteria. Our analysis identified 12 topics, which were grouped into four main themes: origin of the virus; its sources; its impact on people, countries, and the economy; and ways of mitigating the risk of infection. The mean sentiment was positive for 10 topics and negative for 2 topics (deaths caused by COVID-19 and increased racism). The mean for tweet topics of account followers ranged from 2722 (increased racism) to 13,413 (economic losses). The highest mean of likes for the tweets was 15.4 (economic loss), while the lowest was 3.94 (travel bans and warnings).Conclusions: Public health crisis response activities on the ground and online are becoming increasingly simultaneous and intertwined. Social media provides an opportunity to directly communicate health information to the public. Health systems should work on building national and international disease detection and surveillance systems through monitoring social media. There is also a need for a more proactive and agile public health presence on social media to combat the spread of fake news.